1. Field
Methods and apparatuses consistent with exemplary embodiments relate to detecting motion based on a matrix including frequency transform and filtering, and more particularly, to detecting motion of an image by multiplying a calculation matrix that performs frequency domain transform, filtering, and time domain transform in a single operation, with a matrix of a time domain.
2. Description of the Related Art
A general surveillance system includes a surveillance camera to monitor an image captured using the surveillance camera via a monitor and to occasionally store images. The surveillance system requires that a surveillant monitor every single screen or the surveillance system store any images including unnecessary images where no motion is generated, and thus, a human resource is additionally required or space for storing images becomes short.
To solve the above problem, surveillance systems of these days use a motion detection method, in which a load of a surveillance camera is reduced, and frames of two images that are sequentially input are compared with each other for fast motion detection to thereby determine whether a motion is generated and detect only a motion area.
Japanese Patent No. 4526592 discloses a method in which a motion area is detected using a discrete cosine transform method to transform image signals, and a calculation amount related to motion vector detection is reduced.
Also, examples of related art motion detection methods include a temporal difference method, a background subtraction method and a motion detection method. In the temporal difference method, motion estimation using a difference in time domains is used. In the background subtraction method, a fixed background area is removed to extract a motion area, and in the motion detection method, Gaussian modeling is used to distinguish between a foreground and a background to separate out the foreground that includes motion.
According to the related art motion detection methods, the number of images from which motion may be detected at a resolution of a size of 640×840 is about 6 frames/sec, and thus, calculation complexity thereof is high to be used in a real-time surveillance system.